The increased prevalence of diabetes and its significant impact on use of health care services, particularly hospitals, is a concern for health planners. This paper explores the risk factors for all-cause hospitalisation and the excess risk due to diabetes in a large sample of older Australians.

Methods

The study population was 263,482 participants in the 45 and Up Study. The data assessed were linked records of hospital admissions in the 12 months following completion of a baseline questionnaire. All cause and ambulatory care sensitive admission rates and length of stay were examined. The associations between demographic characteristics, socioeconomic status, lifestyle factors, and health and wellbeing and risk of hospitalisation were explored using zero inflated Poisson (ZIP) regression models adjusting for age and gender. The ratios of adjusted relative rates and 95% confidence intervals were calculated to determine the excess risk due to diabetes.

Results

Prevalence of diabetes was 9.0% (n = 23,779). Age adjusted admission rates for all-cause hospitalisation were 631.3 and 454.8 per 1,000 participant years and the mean length of stay was 8.2 and 7.1 days respectively for participants with and without diabetes. In people with and without diabetes, the risk of hospitalisation was associated with age, gender, household income, smoking, BMI, physical activity, and health and wellbeing. However, the increased risk of hospitalisation was attenuated for participants with diabetes who were older, obese, or had hypertension or hyperlipidaemia and enhanced for those participants with diabetes who were male, on low income, current smokers or who had anxiety or depression.

Conclusions

This study is one of the few studies published to explore the impact of diabetes on hospitalisation in a large non-clinical population, the 45 and Up Study. The attenuation of risk associated with some factors is likely to be due to correlation between diabetes and factors such as age and obesity. The increased risk in association with other factors such as gender and low income in participants with diabetes is likely to be due to their synergistic influence on health status and the way services are accessed.

Leaflets produced by the industry were among the hardest to read with an average readability at the 8th grade (8.4 ± 0.1). The readability of leaflets produced by the commercial sector was at the 7th grade (7.1 ± 1.7) and the government at the 6th grade (6.3 ± 1.9). The FKGL consistently yielded readabilities 2 grades below the Fog and SMOG indexes. In the content analyses, 14 essential paediatric oral health topics were noted and Early Childhood Caries (ECC) was identified as the most commonly used jargon term.

Conclusion

Paediatric oral health education materials are readily available, yet their quality and readability vary widely and may be difficult to read for disadvantaged populations in Australia. A redesign of these leaflets while taking literacy into consideration is suggested.

Screening for vascular disease, risk assessment and management are encouraged in general practice however there is limited evidence about the emotional impact on patients. The Health Improvement and Prevention Study evaluated the impact of a general practice-based vascular risk factor intervention on behavioural and physiological risk factors in 30 Australian practices. The primary aim of this analysis is to investigate the psychological impact of participating in the intervention arm of the trial. The secondary aim is to identify the mediating effects of changes in behavioural risk factors or BMI.

Methods

This study is an analysis of a secondary outcome from a cluster randomized controlled trial. Patients, aged 40–65 years, were randomly selected from practice records. Those with pre-existing cardiovascular disease were excluded. Socio-demographic details, behavioural risk factors and psychological distress were measured at baseline and 12 months. The Kessler Psychological Distress Score (K10) was the outcome measure for multi-level, multivariable analysis and a product-of-coefficient test to assess the mediating effects of behaviour change.

Results

Baseline data were available 384 participants in the intervention group and 315 in the control group. Twelve month data were available for 355 in the intervention group and 300 in the control group. The K10 score of patients in the intervention group (14.78, SD 5.74) was lower at 12 months compared to the control group (15.97, SD 6.30). K10 at 12 months was significantly associated with the score at baseline and being unable to work but not with age, gender, change in behavioural risk factors or change in BMI.

Conclusions

The reduction of K10 in the intervention group demonstrates that a general practice based intervention to identify and manage vascular risk factors did not adversely impact on the psychological distress of the participants. The impact of the intervention on distress was not mediated by a change in the behavioural risk factors or BMI, suggesting that there must be other mediators that might explain the positive impact of the intervention on emotional wellbeing.

Prevalence studies usually depend on self-report of disease status in survey data or administrative data collections and may over- or under-estimate disease prevalence. The establishment of a linked data collection provided an opportunity to explore the accuracy and completeness of capture of information about diabetes in survey and administrative data collections.

Methods

Baseline questionnaire data at recruitment to the 45 and Up Study was obtained for 266,848 adults aged 45 years and over sampled from New South Wales, Australia in 2006–2009, and linked to administrative data about hospitalisation from the Admitted Patient Data Collection (APDC) for 2000–2009, claims for medical services (MBS) and pharmaceuticals (PBS) from Medicare Australia data for 2004–2009. Diabetes status was determined from response to a question ‘Has a doctor EVER told you that you have diabetes’ (n = 23,981) and augmented by examination of free text fields about diagnosis (n = 119) or use of insulin (n = 58). These data were used to identify the sub-group with type 1 diabetes. We explored the agreement between self-report of diabetes, identification of diabetes diagnostic codes in APDC data, claims for glycosylated haemoglobin (HbA1c) in MBS data, and claims for dispensed medication (oral hyperglycaemic agents and insulin) in PBS data.

Results

Most participants with diabetes were identified in APDC data if admitted to hospital (79.3%), in MBS data with at least one claim for HbA1c testing (84.7%; 73.4% if 2 tests claimed) or in PBS data through claim for diabetes medication (71.4%). Using these alternate data collections as an imperfect ‘gold standard’ we calculated sensitivities of 83.7% for APDC, 63.9% (80.5% for two tests) for MBS, and 96.6% for PBS data and specificities of 97.7%, 98.4% and 97.1% respectively. The lower sensitivity for HbA1c may reflect the use of this test to screen for diabetes suggesting that it is less useful in identifying people with diabetes without additional information. Kappa values were 0.80, 0.70 and 0.80 for APDC, MBS and PBS respectively reflecting the large population sample under consideration. Compared to APDC, there was poor agreement about identifying type 1 diabetes status.

Conclusions

Self-report of diagnosis augmented with free text data indicating diabetes as a chronic condition and/or use of insulin among medications used was able to identify participants with diabetes with high sensitivity and specificity compared to available administrative data collections.

Many immigrant populations lack access to primary health care. A recently published study on cholesterol screening among immigrant populations in the US found disparities in cholesterol screening in those originating from Mexico, largely due to limited access to healthcare. This inverse care affects immigrants in many destination countries despite their greater health need.

To investigate key patient clinical and demographic characteristics associated with time between colonoscopy and surgery, and choice of treatment centre for colorectal cancer (CRC) patients. This will add to the little published research examining the pathway following CRC diagnosis and prior to surgery.

Design

Retrospective cohort analysis of linked data.

Setting

A population-based sample of people diagnosed August 2004 to December 2007 in New South Wales, Australia.

Time between colonoscopy and surgery, and whether the surgery took place in a specialist cancer centre.

Results

Among the 407 eligible patients analysed, the median time from colonoscopy to surgery was 19 days (IQR 12–29 days). After adjusting for key demographic and clinical characteristics such as age and disease stage, the time was longer for rectal cancer patients and those reporting fair/poor health, although differences in medians were <5 days. 24% (95% CI 20% to 28%) had surgery in a specialist cancer centre, which was more common among people resident in metropolitan areas (37% vs 14% for others, adjusted p=0.001) and those without private health insurance (30% vs 21% for others, adjusted p=0.03).

Conclusions

There do not appear to be systemic issues affecting time from colonoscopy to surgery related to patients' socio-demographic characteristics. However, patients with private insurance and those living in rural areas may be less likely to receive optimal specialist treatment. A more systematic approach might be needed to ensure cancer patients are treated in specialist cancer centres, particularly patients requiring more specialised treatment.

Article summary

Article focus

Investigate key patient clinical and demographic characteristics associated with time between colonoscopy and surgery, and choice of treatment centre for colorectal cancer patients in New South Wales, Australia.

Most existing research has focused on delay prior to diagnosis, and little is known about factors associated with referral to specialist treatment following diagnosis.

Key messages

Rectal cancer cases had slightly longer time to surgery than colon cancer cases.

Treatment in a specialist cancer centre was associated more with patient access than disease characteristics.

We need to ensure that those with the greatest need, such as those with rectal cancer, have access to timely and specialist treatment.

Strengths and limitations of this study

This is one of the first studies to examine the pathway following colorectal cancer diagnosis and prior to surgery, with a relatively large population-based sample of patients.

Surgery was the only treatment we could reliably analyse.

Surgeon specialties were not known so specialist centres were identified as institutions with radiotherapy facilities.

We cannot determine the exact reason for longer time to treatment and it might actually be a positive, possibly reflecting referral to a specialist surgeon or preoperative radiotherapy.

Ongoing care for chronic conditions such as diabetes is best provided by a range of health professionals working together. There are challenges in achieving this where collaboration crosses organisational and sector boundaries. The aim of this article is to explore the influence of power dynamics and trust on collaboration between health professionals involved in the management of diabetes and their impact on patient experiences.

Methods

A qualitative case study conducted in a rural city in Australia. Forty five health service providers from nineteen organisations (including fee-for-service practices and block funded public sector services) and eight patients from two services were purposively recruited. Data was collected through semi-structured interviews that were audio-taped and transcribed. A thematic analysis approach was used using a two-level coding scheme and cross-case comparisons.

Results

Three themes emerged in relation to power dynamics between health professionals: their use of power to protect their autonomy, power dynamics between private and public sector providers, and reducing their dependency on other health professionals to maintain their power. Despite the intention of government policies to support more shared decision-making, there is little evidence that this is happening. The major trust themes related to role perceptions, demonstrated competence, and the importance of good communication for the development of trust over time. The interaction between trust and role perceptions went beyond understanding each other's roles and professional identity. The level of trust related to the acceptance of each other's roles. The delivery of primary and community-based health services that crosses organisational boundaries adds a layer of complexity to interprofessional relationships. The roles of and role boundaries between and within professional groups and services are changing. The uncertainty and vulnerability associated with these changes has affected the level of trust and mistrust.

Conclusions

Collaboration across organisational boundaries remains challenging. Power dynamics and trust affect the strategic choices made by each health professional about whether to collaborate, with whom, and to what level. These decisions directly influenced patient experiences. Unlike the difficulties in shifting the balance of power in interprofessional relationships, trust and respect can be fostered through a mix of interventions aimed at building personal relationships and establishing agreed rules that govern collaborative care and that are perceived as fair.